Litcius/Paper detail

Disparity of ovarian cancer survival between urban and rural settings

Keely Ulmer, Breanna Greteman, Nicholas Cardillo, Anthony Schneider, Megan McDonald, David Bender, Michael J. Goodheart, Jesús González Bosquet

2022International Journal of Gynecological Cancer16 citationsDOIOpen Access PDF

Abstract

OBJECTIVE: To determine if there is a difference in overall survival of patients with epithelial ovarian cancer in rural, urban, and metropolitan settings in the United States. METHODS: test for dichotomous variables. Kaplan-Meier curves estimated survival of patients based on location of residence, and univariate analyses using Cox proportional HR assessed survival based on baseline characteristics. Multivariate analysis was performed to account for significant covariates. Propensity score matching was used to validate the multivariate survival model. For all tests, p<0.05 was considered statistically significant. RESULTS: A total of 111 627 patients were included with a mean age of 62.5 years for metroolitan (range 18-90), 64.0 years for rural (range 19-90) and 63.2 years for urban areas (range 18-90). Of all patients included, 94 290 were in a metropolitan area (counties >1 million population or 50 000-999 999), 15 386 were in an urban area (population of 10 000-49 999), and 1951 were in a rural area (non-metropolitan/non-core population). Univariate Cox proportional hazards models showed clinically significant differences in survival in patients from metropolitan, urban, and rural areas. Multivariate Cox proportional hazards models showed a clinically significant increase in HRs for patients in rural settings (HR 1.17; 95% CI 1.06 to 1.29). Increasing age and stage, non-insured status, non-white race, and comorbidity were also significant for poorer survival. CONCLUSION: Patients with ovarian cancer who live in rural settings with small populations and greater distance to tertiary care centers have poorer survival. These differences hold after controlling for stage, age, and other significant risk factors related to poorer outcomes. To improve clinical outcomes, we need further studies to identify which of these factors are actionable.

Topics & Concepts

MedicineProportional hazards modelMultivariate analysisDemographySurvival analysisMultivariate statisticsPopulationResidenceMetropolitan areaBivariate analysisUnivariateCohortUnivariate analysisCohort studyInternal medicineEnvironmental healthStatisticsPathologyMathematicsSociologyOvarian cancer diagnosis and treatmentGlobal Cancer Incidence and ScreeningBRCA gene mutations in cancer